7th Drug hypersensitivity meeting: part two

No abstract availabl

The utility of yeast as a tool for cell-based, target-directed high-throughput screening

Many Neglected Tropical Diseases (NTDs) have recently been subject of increased focus, particularly with relation to high-throughput screening (HTS) initiatives. These vital endeavours largely rely of two approaches, in vitro target-directed screening using biochemical assays or cell-based screening which takes no account of the target or targets being hit. Despite their successes both of these approaches have limitations; for example, the production of soluble protein and a lack of cellular context or the problems and expense of parasite cell culture. In addition, both can be challenging to miniaturize for ultra (u)HTS and expensive to utilize. Yeast-based systems offer a cost-effective approach to study and screen protein targets in a direct-directed manner within a eukaryotic cellular context. In this review, we examine the utility and limitations of yeast cell-based, target-directed screening. In particular we focus on the currently under-explored possibility of using such formats in uHTS screening campaigns for NTDs

Identifying inhibitors of the Leishmania inositol phosphorylceramide synthase with antiprotozoal activity using a yeast-based assay and ultra-high throughput screening platform

Leishmaniasis is a Neglected Tropical Disease caused by the insect-vector borne protozoan parasite, Leishmania species. Infection affects millions of the world’s poorest, however vaccines are absent and drug therapy limited. Recently, public-private partnerships have developed to identify new modes of controlling leishmaniasis. Drug discovery is a significant part of these efforts and here we describe the development and utilization of a novel assay to identify antiprotozoal inhibitors of the Leishmania enzyme, inositol phosphorylceramide (IPC) synthase. IPC synthase is a membrane-bound protein with multiple transmembrane domains, meaning that a conventional in vitro assay using purified protein in solution is highly challenging. Therefore, we utilized Saccharomyces cerevisiae as a vehicle to facilitate ultra-high throughput screening of 1.8 million compounds. Antileishmanial benzazepanes were identified and shown to inhibit the enzyme at nanomolar concentrations. Further chemistry produced a benzazepane that demonstrated potent and specific inhibition of IPC synthase in the Leishmania cell

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press